MétaCan
Menu
Back to cohort
Record W2130381530 · doi:10.1109/haptic.2010.5444641

Cooperative teleoperation control with projective force mappings

2010· article· en· W2130381530 on OpenAlexafffund
Pawel Malysz, Shahin Sirouspour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTeleoperationMaster/slaveComputer scienceTask (project management)RobotFlexibility (engineering)Control theory (sociology)Transparency (behavior)TeleroboticsOperator (biology)WorkspaceControl engineeringHaptic technologyControl (management)SimulationEngineeringMathematicsMobile robotArtificial intelligenceSystems engineering

Abstract

fetched live from OpenAlex

The performance objectives of multiple-master/single-slave cooperative teleoperation systems typically involve shared control where each master device controls the same degrees of freedom of the slave manipulator. In this paper, the transparency objectives for multi-master/single-slave teleoperation systems are generalized to include projected force mappings. These mappings can divide the control of the slave robot in arbitrarily defined task subspaces among the master devices. Constraint type forces are reflected to the operator(s) consistent with such task division. A provably stable adaptive controller is presented to facilitate the new projected force mappings. Experiments with a planar 3DOF dual-master/single-slave teleoperation system are provided to demonstrate the operation of the proposed cooperation teleoperation control strategy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.175
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2010
Admission routes2
Has abstractyes

Explore more

Same topicTeleoperation and Haptic SystemsFrench-language works237,207